Terarecon, Inc.

University of California

Siemens Healthineers Ag

Terrarecon, Inc.

Robert James Taylor

Tiecheng T Zhao

Junnan Wu

Gang Li

Motoaki Saito

Vikram Simha

Akio Iwase

Chunguang Jia

Tim Frandsen

Benedikt Krueger

Joseph A Martial

Frauke Bentzien

Benedikt Krüger

Sha He

Shiying Hu

Richard I Weiner

Vishal Chodnekar

Ingrid Struman

Gelson Campanatti, Jr

A method is for providing a uniform resource locator. In an embodiment, the method includes receiving a medical data record via an interface, the medical data record being related to a patient; determining the uniform resource locater related to the medical data record via a computation unit, the uniform resource locator including an authorization token based on the medical data record, the medical data record being accessible by following the uniform resource locator; and providing the uniform resource locator with the interface to the patient. By providing a uniform resource locator of an embodiment including an authorization token, access to the medical data record can be granted fast and efficient, e.g. by a patient forwarding the uniform resource locator to another entity (e.g. a physician), while at the same time non-authorized entities cannot access the medical data record due to their lack of the suitable authorization token.

Blockchain-based distribution of medical data records

According to one embodiment, at least a portion of medical information of a patient is displayed within MRCS executed within a local device, the medical information including medical treatment history of the patient. At least a portion of the displayed medical information of the patient is transmitted to a medical imaging processing server over a network, where the transmitted medical information includes a patient identifier (ID) of the patient. Both the at least a portion of patient medical information and one or more medical images are displayed within the MRCS, where the medical images are associated with the patient and rendered by the medical image processing server. A set of icons representing a set of image processing tools is displayed within the MRCS, which when activated by a user, allow an image to be manipulated by the imaging processing server.

Integration of medical software and advanced image processing

Techniques for providing medical image processing training are described herein. According to one embodiment, at least one medical image associated with a medical image processing training course (MIPTC) is displayed in a first display area. An instruction is displayed in a second display area, where the instruction requests a user to perform a quantitative determination on at least a portion of a body part within the medical image displayed in the first display area. In response to a user action from the user, the requested determination is performed on the displayed medical image. It is determined automatically without user intervention at least one quantitative value representing a result of the user action. The quantitative value is compared to a predefined model answer.

Training and testing system for advanced image processing

According to one embodiment, workflow templates are maintained, each workflow template including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. In response to a request for processing medical image data from a user, a user identifier (ID) that identifies the user is automatically determined based on the request. At least one of the workflow templates that is specifically configured to process medical image data associated with the user is identified based on the user ID. One or more image processing operations defined by the identified workflow template are performed on the medical image data, generating a scene corresponding to an image view representing the medical image data. The scene associated with each of the workflow stages is stored in a persistent storage, where a scene includes metadata used to recreate a corresponding medical image view subsequently.

Workflow template management for medical image data processing

A cloud server receives a request for accessing medical image data from a client device, where the cloud server provides image processing services to users in image processing steps, resulting in image views. User privileges of a user are determined for accessing the medical image data. In response to receiving a command having a selection of an image view from the client device, the cloud server provides the medical image data based on the selected one or more image views. The user interactions of the user with the medical image data via the selected image views are tracked, including tracking how long in time the user takes to complete a particular medical image processing step. An analysis is performed on the tracked user interactions to determine an overall usage trend of the image views.

Cloud-based medical image processing system with tracking capability

A cloud server receives a request for accessing medical image data from a client device, where the cloud server provides image processing services to users in image processing steps, resulting in image views. User privileges of a user are determined for accessing the medical image data. In response to receiving a command having a selection of an image view from the client device, the cloud server provides the medical image data based on the selected one or more image views. The user interactions of the user with the medical image data via the selected image views are tracked, including tracking how much time the user takes to complete a particular medical image processing step. The tracked user interactions are stored in a persistent storage, and an analysis is performed on the tracked user interactions stored in the persistent storage to determine an overall usage trend of the image views.

According to one embodiment, workflow templates are stored, each including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. Each workflow stage defines one or more image processing operations to be performed. At least one workflow stage generates metadata specifying a parameter to be used by another workflow stage for processing a corresponding medical image. In response to medical image data received, at least one of the image processing operations defined by the workflow stages is performed on the medical image data. A scene is generated for each of the workflow stages representing an image view representing the medical image data. In response to a save or validate command received from a user, the scene associated with each of the workflow stages is stored in a persistent storage, which can be used to recreate a corresponding medical image view subsequently.

According to one embodiment, a cloud server receives over a network a request for accessing three-dimensional (3D) medical image data from a first user, where the cloud server provides image processing services to a plurality of users using a plurality of image processing tools provided by the cloud server. The cloud server determines user privileges of the users for accessing the 3D medical image data, where the user privileges are related to the 3D medical image data. The 3D medical image data was captured by a medical imaging device and stored in a storage associated with the cloud server. The availability of the image processing tools is limited to the user to process the 3D medical image data based on the user privileges.

Cloud-based medical image processing system with access control

According to one embodiment, a local device receives 3D medical image data captured by a medical imaging device. The 3D medical image is anonymized by removing certain metadata associated with the 3D medical image data based on an anonymization template. The local device automatically uploads the anonymized 3D medical image data to a cloud server over a network based on a set of one or more rules, using a network connection established via an internet port of the local device. The cloud server is configured to provide medical image processing services to a plurality of users using a plurality of image processing tools provided by the cloud server.

Cloud-based medical image processing system with anonymous data upload and download

Some embodiments of a workflow management system to process medical image data generated by a medical imaging device have been presented. In one embodiment, a user selects a workflow template with a predefined set of image processing stages, and applies the workflow template to the medical image data. Each of the predefined set of image processing stages in the workflow template includes one or more image processing operations. Each of the image processing operations is capable of generating metadata for processing the medical image data. The medical image data is then processed through each of the predefined image processing stages. The result of processing is a collection of metadata. Each metadata in the collection can be applied to the medical image data to generate a medical image view.

The current invention provides novel antiangiogenic peptides which correspond to about 133 consecutive amino acids of the N-terminal sequence of growth hormone.

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San Francisco, CA, United States of America

Robert James Taylor